The primary goal of an investment vehicle is to provide exceptional returns for its investors. One component of an investment vehicle's returns is the returns of the underlying assets that comprise the holdings of the investment vehicle, such as stocks held in a mutual fund. To that aim, financial services firms allocate significant effort and capital to help portfolio managers and analysts identify those assets (or derivatives thereof) that are likely to provide desirable results for the fund, and that will generally outperform other assets and the overall market.
In general, investment portfolio management techniques can be classified as either active management or passive management. Active management, conventionally, describes methods in which the assets (or other underlying investment vehicles) are selected as components of a portfolio based on one or more economic and financial statistics, analyses performed by business analysts, technical trends or some combination of these or other elements. Furthermore, decisions of whether to buy, sell or hold a particular asset or alter a fund's weighting in an asset, industry or geographic market segment are typically performed by individuals (e.g., portfolio and/or fund managers in the case of mutual funds). Such funds are often prone to large variations in performance and the operating costs attributed to many actively managed funds can be significant, and therefore erode returns.
In contrast, passive management (also known as index-based management), relies on pre-defined indices (e.g., the STANDARD & POOR'S 500, the WILSHIRE 5000, etc.), to determine the assets held within a portfolio and the weighting attributed to each asset such that the portfolio's holdings closely approximate those that make up the particular index on which it is based. Some of the advantages of passive management techniques include lower trading costs, lower management costs, and very low fluctuations in performance relative to the underlying index on which the portfolio is based.
Unlike active management techniques, the weightings of assets in a passively managed portfolio are typically based on the relative market capitalization of the assets that comprise the index or, in some cases, the assets are weighted equally. Advantages of using market capitalization weighting as the basis for a passive portfolio include that the index (and therefore a portfolio built on it) remains continually “in balance” as market prices for the included assets change. Market capitalization weighting is also supported by modern portfolio theory, which implies that given certain assumptions, market capitalization weighting generates portfolios that maximize expected risk-adjusted return and is therefore optimal. However, one drawback of capitalization-weighted portfolios is that they can be influenced by valuation errors. For example, investors are motivated to value assets to reflect attributes such as risk and growth, but at any given point in time assets may be undervalued, overvalued, or correctly valued. While investors will attempt to value assets to reflect asset attributes, assets with low valuation may tend to reflect undervaluation errors and assets with high valuation may tend to reflect overvaluation errors.
While attributing a disproportionate amount of assets to lower market capitalization assets (either individually or in groups) may provide certain benefits, it does not consider other possible techniques for evaluating the underlying company (in the case of an equity) that may be indicative of an under priced asset. Nor does such an approach provide any methodology for determining, for example, the optimal groupings (and resultant group weightings) based on such techniques. As a result, opportunities to outperform the index and the market are missed. What is needed, therefore, is an investment vehicle (and supporting techniques for designing and managing such an investment vehicle) that takes advantage of certain operational aspects generally associated with passively managed capitalization-weighted funds, but uses additional statistical analyses and weighting techniques to position a portfolio to benefit from valuation errors as market conditions change, and thereby provide exceptional long-term risk-adjusted returns to investors.